To　motivate　data　owners’　(DOs’)　trading　willingness,　the　existing　incentive　mechanisms　allow　DOs　to　independently　disturb　data　following　data　consumer’s　(DC’s)　availability　requirement.　However,　they　cannot　motivate　DOs’　honest　disturbance,　which　is　attributed　to　DOs’　independent　disturbance　without　any　supervision.　Thus,　we　implement　an　incentive　mechanism　for　privacy　preserved　data　trading　with　verifiable　data　disturbance　where　an　honest-but-curious　disturbance　generator　(DG)　is　additionally　introduced　to　supervise　DOs’　local　disturbance　and　assist　disturbance　verification　between　DOs　and　DC.　Specifically,　DG　generates　the　disturbance　strategies　and　secretly　distributes　to　DOs　following　private　information　retrieval,　guaranteeing　DOs’s　local　disturbance’s　privacy　and　verifiability　with　our　proposed　three-level　verification　algorithm.　Subsequently,　we　model　the　trading　as　a　game　and　disturbance　verification　results　determine　the　compensation　and　punishment　for　trading　bilateral　utilities　following　Nash　Equilibrium　where　DOs　honestly　disturb　data.　Theoretical　analysis　shows　that　DOs　are　motivated　to　honestly　disturb　data　and　their　raw　data　privacy　is　preserved.　Extensive　experiments　using　the　real-world　dataset　demonstrate　that　the　deviating　DOs　in　our　scheme　can　be　verified　with　a　probability　of　more　than　90%　and　the　statistical　result　accuracy　can　be　improved　by　more　than　80%　compared　with　the　existing　works.　©　2004-2012　IEEE.　All　rights　reserved.